Most of the traditional methods for shape classification are based on contour. They often encounter difficulties when dealing with classes that have large nonlinear variability, es...
Xingwei Yang, Xiang Bai, Deguang Yu, Longin Jan La...
In many real-world applications, Euclidean distance in the original space is not good due to the curse of dimensionality. In this paper, we propose a new method, called Discrimina...
Supervised learning is difficult with high dimensional input spaces and very small training sets, but accurate classification may be possible if the data lie on a low-dimensional ...
Hyperlink Structure is widely used in the hypertext classification, but it has not been paid enough attention. We propose a hyperlink classification approach to improve PageRank a...
In this paper, the problem of discovering anomalies in a large-scale network based on the data fusion of heterogeneous monitors is considered. We present a classification of anoma...